https://github.com/elbayadm/OnlineMT-Evaluation
공식 코드Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English
Papers with Code 아카이브
Machine Translation
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Machine translation is the task of translating a sentence in a source language to a different target language.
Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.
One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.
<span style="color:grey; opacity: 0.6">( Image credit: Google seq2seq )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/elbayadm/attn2d
공식 코드Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction
https://github.com/elbayadm/attn2d/tree/master/examples/waitk
공식 코드Efficient Wait-k Models for Simultaneous Machine Translation
https://github.com/elbayadm/seq2seq
공식 코드Token-level and sequence-level loss smoothing for RNN language models
https://github.com/elbria/ex-semdiv
공식 코드https://github.com/eleanorjiang/blonde
공식 코드BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation
https://github.com/elenigkove/genderbias_en-el_mt
공식 코드https://github.com/elliottyan/gpt_versus_mt_experts
공식 코드https://github.com/elliottyan/refutebench
공식 코드RefuteBench: Evaluating Refuting Instruction-Following for Large Language Models
https://github.com/emjotde/mosesdecoder_nmt
공식 코드https://github.com/emnlpanon/mt-paper
공식 코드Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional Tagging
https://github.com/enscma2/categorical-modularity
공식 코드https://github.com/epfml/collaborative-attention
공식 코드https://github.com/eric-mitchell/macaw
공식 코드Offline Meta-Reinforcement Learning with Advantage Weighting
https://github.com/erichen0615/controldag
공식 코드https://github.com/ericongma/e2timt
공식 코드E2TIMT: Efficient and Effective Modal Adapter for Text Image Machine Translation
https://github.com/esalesky/visrep
공식 코드Robust Open-Vocabulary Translation from Visual Text Representations
https://github.com/esalesky/xnmt-devel
공식 코드https://github.com/esdurmus/Wikilingua
공식 코드WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization
https://github.com/espnet/espnet
공식 코드https://github.com/ethch18/specializing-multilingual
공식 코드Specializing Multilingual Language Models: An Empirical Study
https://github.com/euranova/orphanet_translation
공식 코드https://github.com/euranova/wikidata_property_extraction
공식 코드https://github.com/eval4nlp/sharedtask2023
공식 코드The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics
https://github.com/ewdowiak/Sicilian_Translator
공식 코드https://github.com/exgc/avmust-ted
공식 코드https://github.com/exqrch/indonesiannmt
공식 코드https://github.com/facebookresearch/CodeGen
공식 코드https://github.com/facebookresearch/DisCo
공식 코드Non-Autoregressive Machine Translation with Disentangled Context Transformer
https://github.com/facebookresearch/LASER
공식 코드Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
https://github.com/facebookresearch/MIXER
공식 코드https://github.com/facebookresearch/MLQA
공식 코드MLQA: Evaluating Cross-lingual Extractive Question Answering
https://github.com/facebookresearch/MUSE
공식 코드https://github.com/facebookresearch/Mask-Predict
공식 코드Mask-Predict: Parallel Decoding of Conditional Masked Language Models
https://github.com/facebookresearch/UnsupervisedMT
공식 코드https://github.com/facebookresearch/analyzing-uncertainty-nmt
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.